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Authors: Hamid R. Chinaei ; Brahim Chaib-draa and Luc Lamontagne

Affiliation: Laval University, Canada

ISBN: 978-989-8111-66-1

Keyword(s): Learning, Spoken Dialogue Systems.

Related Ontology Subjects/Areas/Topics: Agents ; Applications ; Artificial Intelligence ; Cognitive Robotics ; Conversational Agents ; Industrial Applications of AI ; Informatics in Control, Automation and Robotics ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Natural Language Processing ; Pattern Recognition ; Robotics and Automation ; Soft Computing ; Symbolic Systems ; Uncertainty in AI

Abstract: A common problem in spoken dialogue systems is finding the intention of the user. This problem deals with obtaining one or several topics for each transcribed, possibly noisy, sentence of the user. In this work, we apply the recent unsupervised learning method, Hidden Topic Markov Models (HTMM), for finding the intention of the user in dialogues. This technique combines two methods of Latent Dirichlet Allocation (LDA) and Hidden Markov Model (HMM) in order to learn topics of documents. We show that HTMM can be also used for obtaining intentions for the noisy transcribed sentences of the user in spoken dialogue systems. We argue that in this way we can learn possible states in a speech domain which can be used in the design stage of its spoken dialogue system. Furthermore, we discuss that the learned model can be augmented and used in a POMDP (Partially Observable Markov Decision Process) dialogue manager of the spoken dialogue system.

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Paper citation in several formats:
R. Chinaei H.; Chaib-draa B.; Lamontagne L. and (2009). LEARNING USER INTENTIONS IN SPOKEN DIALOGUE SYSTEMS.In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8111-66-1, pages 107-114. DOI: 10.5220/0001663801070114

@conference{icaart09,
author={Hamid {R. Chinaei} and Brahim Chaib{-}draa and Luc Lamontagne},
title={LEARNING USER INTENTIONS IN SPOKEN DIALOGUE SYSTEMS},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2009},
pages={107-114},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001663801070114},
isbn={978-989-8111-66-1},
}

TY - CONF

JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - LEARNING USER INTENTIONS IN SPOKEN DIALOGUE SYSTEMS
SN - 978-989-8111-66-1
AU - R. Chinaei, H.
AU - Chaib-draa, B.
AU - Lamontagne, L.
PY - 2009
SP - 107
EP - 114
DO - 10.5220/0001663801070114

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